Earticle

The ARINC-653 standard architecture for flight software specifies an application executive (APEX) which furnishes an application programming interface of fifty-one routines. APEX enables the development of portable applications, providing a strict time and space partitioning for their execution along with intra- and inter-partition communication facilities. This architecture also defines a hierarchical health management framework for error detection and recovery. However, in every partition, asynchronously concurrent processes or threads may include concurrency bugs such as unintended data races which are common and difficult to remove by testing. To reinforce the capability of the ARINC-653 health management system and to increase the reliability of flight software, this article describes the development and the configuration of an on-the-fly race healing framework into a simulated ARINC-653 platform which provides real ARINC-653 programming interface. The experimental results allow us to argue that our race healing framework is practical enough to be configured under the ARINC-653 partitions.

This paper considers the blind multiuser reception problem for Direct Sequence Code Division Multiple Access (DS-CDMA) systems. A hybrid approach to the blind reception of linear multiple-input multiple-output (MIMO) channels is taken up. We consider the problem of blind detection of multiuser CDMA signals in a space time scenario. The channel is assumed to have a small scale flat fading behaviour. A two step adaptive reception method used. The receiver has the knowledge of only the spreading code of interest. The higher order statistical (HOS) technique known as Independent Component Analysis (ICA) is employed for the signal separation. The performance of this technique in the small scale flat fading space time scenario with different types of user signature codes is analyzed through various simulations.

QoS multicast routing is a non-linear combinatorial optimization problem that arises in many multimedia applications. Providing QoS support is crucial to guarantee effective transportation of multimedia service in multicast communication. Computing the band-widthdelay constrained least cost multicast routing tree is an NP-complete problem. In this paper, a novel heuristic QoS multicast routing algorithm with bandwidth and delay constraints is proposed. The algorithm applies the discrete particle swarm optimization (PSO) algorithm to optimally search the solution space for the optimal multicast tree which satisfies the QoS requirement. New PSO operators have been introduced to modify the original PSO velocity and position update rules to adapt to the discrete solution space of the multicast routing problem. A new adjustable PSO-GA hybrid multicast routing algorithm which combines PSO with genetic operators was proposed. The proposed hybrid technique combines the strengths of PSO and GA to realize the balance between natural selection and good knowledge sharing to provide robust and efficient search of the solution space. Two driving parameters are utilized in the adjustable hybrid model to optimize the performance of the PSO-GA hybrid by giving preference to either PSO or GA. Simulation results show that with the correct combination of GA and PSO the hybrid algorithm outperforms both the standard PSO and GA models. The flexibility in the choice of parameters in the hybrid algorithm improves the ability of the evolutionary operators to generate strong-developing individuals that can achieve faster convergence and avoids premature convergence to local optima.

Clustering is a process of discovering group of objects such that the objects of the same group are similar, and objects belonging to different groups are dissimilar. A number of clustering algorithms exist that can solve the problem of clustering, but most of them are very sensitive to their input parameters. Minimum Spanning Tree clustering algorithm is capable of detecting clusters with irregular boundaries. A density-based notion of clusters which is designed to discover clusters of arbitrary shape. In this paper we propose a combined approach based on Minimum Spanning Tree based clustering and Density-based clustering for noise-free high density best number of clusters. The algorithm uses a new cluster validation criterion based on the geometric property of data partition of the data set in order to find the proper number of clusters at each level. The algorithm works in two phases. The first phase of the algorithm produces subtrees (noise-free clusters). The second phase finds high density clusters from the subtrees.

This paper comprises two parts, the first deals with the conception of a class of Hybrid Granular Min-Max Fuzzy-Neuro Relational Learners, for which a learning scheme was devised that uses an exhaustive search over the fuzzy partitions of involved variables, automatic fuzzy hypotheses generation, formulation and testing, and successive approximation procedure of Min-Max relational equations. The main idea is to start learning from coarse fuzzy partitions of the involved input variables and proceed progressively toward fine-grained partitions until finding the appropriate partitions that fit the data. According to the complexity of the problem at hand, it learns the whole structure of the fuzzy system, i.e. conjointly appropriate fuzzy partitions, appropriate fuzzy production rules, their number and their associated membership functions. The fuzzy relational calculus in the context of approximation of fuzzy relations equations, constitutes a good candidate tool in machine learning, and is especially useful for dealing with inverse problems. The second part deals with verification and validation issues of such learners, validation brings us to a systematic study of value approximation performed during the inference (recall) phase. We provide a rigorous formal mathematical proof that Min-Max rule preserves the property of approximation when it is applied to entities characterized by approximately equal fuzzy values. Hence, using standard Min-Max is a suitable choice in building Hybrid Granular Fuzzy-Neuro or Neuro-Fuzzy Relational Learners, as it is accepted that generalization capability is proportional to value approximation.

Voiceprint Recognition System also known as a Speaker Recognition System (SRS) is the best-known commercialized forms of voice Biometrics. Automated speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. In contrast to other biometric technologies which are mostly image based and require expensive proprietary hardware such as vendor’s fingerprint sensor or iris-scanning equipment, the speaker recognition systems are designed for use with virtually any standard telephone or on public telephone networks. The ability to work with standard telephone equipment makes it possible to support broad-based deployments of voice biometrics applications in a variety of settings. In automated speaker recognition the speech signal is processed to extract speaker-specific information. These speaker specific informations are used to generate voiceprint which cannot be replicated by any source except the original speaker. This makes speaker recognition a secure method for authenticating an individual since unlike passwords or tokens; it cannot be stolen, duplicated or forgotten. This literature survey paper gives brief introduction on SRS, and then discusses general architecture of SRS, biometric standards relevant to voice/speech, typical applications of SRS, and current research in Speaker Recognition Systems. We have also surveyed various approaches for SRS

The Recursive Least Squares (RLS) algorithm is renowned for its rapid convergence but in some scenarios it fails to show swiftness required by several applications. Such failure may result due to different limiting conditions. Gain vector plays an essential role in the performance of RLS algorithm. This paper proposes a modification in Gain vector that results in RLS algorithm performing much better in perspective of convergence, without adding significant complexity. Simulation results are presented which prove the authenticity of the finding, and comparison with conventional RLS algorithm is presented.